Salesforce
Company
Lead Data Scientist | LMTS
Job Description
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Software EngineeringJob Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
Position Overview
We are seeking an experienced Lead Data Scientist (LMTS) to drive data science innovation in predictive modeling and AI within Salesforce’s infrastructure domain. As a technical leader, you will design, deploy, and operationalize advanced forecasting and anomaly detection models at scale. You will also shape the roadmap for integrating foundation models and LLMs into production forecasting workflows, enabling faster root cause analysis, proactive recommendations, and automated insights for stakeholders across capacity, cost, and infrastructure planning.
This is a hands-on technical leadership role: you will not only build models but also set technical direction, mentor other data scientists, and raise the bar for reproducibility, scalability, and explainability across our platform.
Responsibilities
Lead the design, development, and deployment of high-impact forecasting models used across capacity planning, FinOps, and infrastructure cost management.
Partner with cross-functional leaders (capacity planners, finance, engineering) to shape requirements, influence priorities, and ensure models solve real-world infrastructure challenges.
Act as a multiplier on the team by mentoring SMTS/MTS data scientists, providing technical coaching, and instilling best practices in reproducibility, CI/CD, monitoring, and model lifecycle management.
Drive the adoption of LLMs and foundation models in applied infrastructure management — defining architectures, guiding experimentation, and leading integration into production workflows.
Own end-to-end quality of deliverables, ensuring models are accurate, robust, observable, and aligned with trust and security standards.
Contribute to the broader data science community at Salesforce by sharing methodologies, influencing platform standards, and reviewing technical designs across teams.
Champion continuous improvement in data science processes, proactively addressing tech debt, standardizing pipelines, and defining metrics (SLIs/SLOs) to measure forecast performance.
Qualifications
Advanced technical degree in a relevant field (Computer Science, Statistics, Operations Research, Applied Math, etc.).
8+ years of industry experience building and deploying machine learning solutions (time series forecasting experience strongly preferred).
Proven ability to lead technical direction for data science projects, mentor junior members, and influence cross-team engineering practices.
Demonstrated success delivering production-grade ML/AI systems in cloud environments (AWS/GCP), including monitoring, CI/CD, and observability.
Strong expertise in time series forecasting and ML methods; familiarity with foundation models and LLMs in applied data science.
Proficiency in Python and modern DS/ML tools (mlFlow, Airflow, Docker, Spark, SQL, Pandas/Sklearn).
Strong communicator, capable of influencing both technical and non-technical stakeholders, and of synthesizing complex data science concepts into actionable insights.
Track record of driving measurable business impact through data science solutions at scale.
BENEFITS & PERKS
Comprehensive benefits package including well-being reimbursement, generous parental leave, adoption assistance, fertility benefits, and more!
World-class enablement and on-demand training with Trailhead.com
Exposure to executive thought leaders and regular 1:1 coaching with leadership
Volunteer opportunities and participation in our 1:1:1 model for giving back to the community
For more details, visit https://www.salesforcebenefits.com/
Unleash Your Potential
When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.
Accommodations
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Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
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